Enhancing the power of Web search engines by means of fuzzy query

Commercial Web search engines such as Yahoo!, Google, etc., have been defined which manage information only in a crisp way (i.e., keyword-based). Their query languages do not allow the expression of preferences or vagueness. They generally return many Web pages irrelevant to user's query. In order to handle these problems, we propose the Perception Index (PI) that contains attributes associated with a focal keyword restricted by fuzzy term(s) used in fuzzy queries on the Internet. The PI assists the user to reflect his/her perception in the process of query. If we integrate the Document Index (DI) used in commercial Web search engines with the proposed PI, we can handle both crisp terms (keyword-based) and fuzzy terms (perception-based). In this respect, the proposed approach is softer than the keyword-based approach. The PI brings somewhat closer to natural language. It is a further step toward a human-friendly, natural language-based interface for Web searching. Consequently, Internet users can narrow thousands of hits to the few that users really want. In this respect, the PI provides a new tool for targeting queries that users really want. In this paper, we also present a personalized search and ranking based on the PI.